Shiqi Zhang
Papers
1
Total Citations
4
H-Index
1
About
Shiqi Zhang is a researcher specializing in intelligent optimization algorithms, sustainable manufacturing, and robotics-assisted disassembly systems. Their work sits at the intersection of operations research and green manufacturing, addressing one of modern industry's most pressing challenges: the efficient and environmentally responsible handling of end-of-life industrial products. Zhang's most notable contribution, "An Improved Tabu Search Algorithm for Multi-robot Hybrid Disassembly Line Balancing Problems" (2022), tackles the complex combinatorial optimization challenge of coordinating multiple robots in disassembly line operations — a critical step toward automating recycling and waste reduction processes in the face of rapid global industrialization. By refining the classical Tabu Search metaheuristic, Zhang advances the field's ability to balance competing operational constraints while minimizing industrial waste, directly responding to the environmental pressures created by large-scale manufacturing expansion. Although early in their citation trajectory with 4 citations, the work addresses a highly relevant and growing area as industries worldwide grapple with sustainability mandates and circular economy principles. Zhang's research holds strong potential to influence future automated disassembly systems and resource recovery strategies across multiple manufacturing sectors.
Research Focus
Key Achievements
Top Papers
- 1